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1.
J Cancer Res Ther ; 16(6): 1323-1330, 2020.
Article in English | MEDLINE | ID: mdl-33342791

ABSTRACT

PURPOSE: Different dose calculation algorithms (DCAs) predict different dose distributions for the same treatment. Awareness of optimal model parameters is vital for estimating normal tissue complication probability (NTCP) for different algorithms. The aim is to determine the NTCP parameter values for different DCAs in left-sided breast radiotherapy, using the Lyman-Kutcher-Burman (LKB) model. MATERIALS AND METHODS: First, the methodology recommended by International Atomic Energy Agency TEC-DOC 1583 was used to establish the accuracy of dose calculations of different DCAs including: Monte Carlo (MC) and collapsed cone algorithms implemented in Monaco, pencil beam convolution (PBC) and analytical anisotropic algorithm (AAA) implemented in Eclipse, and superposition and Clarkson algorithms implemented in PCRT3D treatment planning systems (TPSs). Then, treatment planning of 15 patients with left-sided breast cancer was performed by the mentioned DCAs and NTCP of the left-lung normal tissue were calculated for each patient individually, using the LKB model. For the PB algorithm, the NTCP parameters were taken from previously published values and new model parameters obtained for each DCA, using the iterative least squares methods. RESULTS: For all cases and DCAs, NTCP computation with the same model parameters resulted in >15% deviation in NTCP values. The new NTCP model parameters were classified according to the algorithm type. Thus, the discrepancy of NTCP computations was reduced up to 5% after utilizing adjusted model parameters. CONCLUSIONS: This paper confirms that the NTCP values for a given treatment type are different for the different DCAs. Thus, it is essential to introduce appropriate NTCP parameter values according to DCA adopted in TPS, to obtain a more precise estimation of lung NTCP. Hence, new parameter values, classified according to the DCAs, must be determined before introducing NTCP estimation in clinical practice.


Subject(s)
Algorithms , Breast Neoplasms/radiotherapy , Lung/radiation effects , Radiotherapy Planning, Computer-Assisted/methods , Breast Neoplasms/pathology , Female , Humans , Monte Carlo Method , Probability , Radiotherapy Dosage
2.
Biomed Phys Eng Express ; 7(1)2020 12 21.
Article in English | MEDLINE | ID: mdl-35037902

ABSTRACT

Objective: MR-linac machines are being developed for image-guided radiation therapy but the magnetic field of such machines could affect dose distributions. The purpose of this work was to evaluate the effect of a magnetic field on linac beam dosimetric parameters including penumbra for circular cones used in radiosurgery.Methods: Monte Carlo simulation was conducted for a linac machine with circular cones at 6 MV beam. A homogenous magnetic field of 1.5 T was applied transversely and parallel to the radiation beam. Percentage depth dose (PDD) and beam profiles in a water phantom with and without the magnetic field were calculated.Results: The results have shown that when the magnetic field is applied transversely, the PDDs in the water phantom differ in the buildup region and distant part of PDD curves. The beam profiles at three different depths are all significantly different from those without the magnetic field. The penumbra is greater when a magnetic field has been applied.Conclusion: Linear accelerator-based SRT and SRS use small circular cones. The beam penumbra for these cones can change in the presence of a magnetic field. The perturbation of dose distribution has been also observed in a patient plan due to the presence of a magnetic field. The results of this study show that dose distributions in the presence of a magnetic field must be considered for MR-guided radiotherapy treatments.


Subject(s)
Radiosurgery , Humans , Magnetic Fields , Particle Accelerators , Radiosurgery/methods , Radiotherapy Dosage , Radiotherapy Planning, Computer-Assisted/methods
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